A Sequential Minimal Optimization Algorithm for the All-Distances Support Vector Machine-Reference-Cited by-同舟云学术

A Sequential Minimal Optimization Algorithm for the All-Distances Support Vector Machine

Published:2010 Issue: Volume: Page:484-491
ISSN:0302-9743
Container-title:Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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Author:

Candel Diego,Ñanculef Ricardo,Concha Carlos,Allende Héctor

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-16687-7_64

Reference21 articles.

1. Blake, C., Merz, C.: UCI repository of machine learning databases (1998), http://mlr.cs.umass.edu/ml/index.html

2. Candel, D.: Source code of the smo algorithm for the ad-svm, http://git.inf.utfsm.cl/?p=dcontard.git;a=summary

3. Candel, D.: Algoritmo tipo SMO para la AD-SVM aplicado a Clasificación Multicategoría. Master’s thesis, Universidad Técnica Federico Santa María, Valparaíso, Chile (2010), http://www.alumnos.inf.utfsm.cl/~dcontard/tesis.pdf

4. Chang, C.C., Lin, C.J.: Libsvm data: Classification, multi-class (2001), http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass.html

5. Chen, P.H., Fan, R.E., Lin, C.J.: A study on SMO-type decomposition methods for support vector machines. IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council 17(4), 893–908 (2006)

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